AbstractBackgroundThe world population is rapidly aging, and the prevalence of dementia due to Alzheimer’s disease (AD) and related disorders is correspondingly increasing. Thus, detecting cognitive decline in older individuals is an urgent public health concern. There is a need for brief, practical, standardized measures that are sensitive to cognitive decline and can be broadly deployed in diverse settings. Advancing Reliable Measurement in Alzheimer's Disease and Cognitive Aging (ARMADA) aims to meet this need by validating the NIH Toolbox for Assessment of Neurological and Behavioral Function® (NIHTB®) in individuals ages 65 to 85 who are cognitively healthy or diagnosed with either mild cognitive impairment (MCI) or dementia of the Alzheimer type (AD). A broad range of clinical and healthy samples have been recruited to date, including an African American sample and a Spanish‐speaking Hispanic sample to reflect the diversity of people affected by cognitive decline and to enable validation of the Spanish NIHTB. We will present baseline NIHTB results for each sample.MethodIndividuals age 65 or older who are either cognitively normal or diagnosed with cognitive impairment (MCI or early AD) have been recruited from nine clinical centers with established research cohorts. Participants complete the NIHTB and gold standard neuropsychological assessment at baseline. AD biomarkers, including PET beta amyloid level, CSF tau, and APoE genotype, are also available.ResultAs of January 2020, 656 participants have completed the baseline assessment. Early results indicate the NIHTB Cognition battery, as well as individual measures, successfully discriminates among MCI, AD and healthy controls in the general population sample (N=259). Baseline data collection for the African American and Hispanic samples will be largely complete by June 2020, and initial results will be presented.ConclusionInitial baseline results from the ARMADA study provide evidence that the NIHTB discriminates among older individuals with normal cognition, MCI, and early AD. Two annual longitudinal follow‐ups will evaluate how well NIH Toolbox measures predict future cognitive decline, their sensitivity to change and their association with AD biomarkers.